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NVIDIA’s Perspective: Closing the Time-to-Market Gap: Practical GPU Gains in Semiconductor Manufacturing
AI is driving a new wave of innovation across semiconductor manufacturing, but realizing meaningful gains requires more than adding compute. In this session, NVIDIA explores how accelerated computing, AI-driven physics models, digital twins, and agentic AI are being applied across the semiconductor lifecycle—from design and mask creation to process development, fab operations, packaging, and system integration.
What you’ll learn:
- Key opportunities to accelerate semiconductor design, simulation, and manufacturing workflows with GPU computing.
- How AI physics and digital twin technologies are improving modeling, process development, and fab optimization.
- Real-world examples of collaboration between NVIDIA, Synopsys, and Applied Materials to advance semiconductor innovation.
- Practical applications of agentic AI to enhance engineering productivity, decision-making, and workflow efficiency.
- NVIDIA’s vision for AI-powered semiconductor manufacturing, from intelligent automation to autonomous fab operations.
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Featured Speaker
Da Yang
Senior Director of Product, Semiconductor and EDA
Da Yang is Senior Director of Product at NVIDIA, where he leads the AI product development for Semiconductor and EDA applications. Before joining NVIDIA, Da was Vice President of Technology at Tokyo Electron America, leading new product development for fabless design customers. Prior to Tokyo Electron, Da had worked at Qualcomm and IBM covering various design optimization and process development roles. He has coauthored a book and published over 30 technical papers, holds over 20 granted U.S. patents.
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